dorsal/arxiv
View SchemaA "black-box" re-weighting analysis can correct flawed simulation data, after the fact
| Authors | F. Marty Ytreberg, Daniel M. Zuckerman |
|---|---|
| Categories | |
| ArXiv ID | physics/0609194 |
| URL | https://arxiv.org/abs/physics/0609194 |
Abstract
There is a great need for improved statistical sampling in a range of physical, chemical and biological systems. Even simulations based on correct algorithms suffer from statistical error, which can be substantial or even dominant when slow processes are involved. Further, in key biomolecular applications, such as the determination of protein structures from NMR data, non-Boltzmann-distributed ensembles are generated. We therefore have developed the "black-box" strategy for re-weighting a set of configurations generated by arbitrary means to produce an ensemble distributed according to any target distribution. In contrast to previous algorithmic efforts, the black-box approach exploits the configuration-space density observed in a simulation, rather than assuming a desired distribution has been generated. Successful implementations of the strategy, which reduce both statistical error and bias, are developed for a one-dimensional system, and a 50-atom peptide, for which the correct 250-to-1 population ratio is recovered from a heavily biased ensemble.
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"abstract": "There is a great need for improved statistical sampling in a range of\nphysical, chemical and biological systems. Even simulations based on correct\nalgorithms suffer from statistical error, which can be substantial or even\ndominant when slow processes are involved. Further, in key biomolecular\napplications, such as the determination of protein structures from NMR data,\nnon-Boltzmann-distributed ensembles are generated. We therefore have developed\nthe \"black-box\" strategy for re-weighting a set of configurations generated by\narbitrary means to produce an ensemble distributed according to any target\ndistribution. In contrast to previous algorithmic efforts, the black-box\napproach exploits the configuration-space density observed in a simulation,\nrather than assuming a desired distribution has been generated. Successful\nimplementations of the strategy, which reduce both statistical error and bias,\nare developed for a one-dimensional system, and a 50-atom peptide, for which\nthe correct 250-to-1 population ratio is recovered from a heavily biased\nensemble.",
"arxiv_id": "physics/0609194",
"authors": [
"F. Marty Ytreberg",
"Daniel M. Zuckerman"
],
"categories": [
"physics.comp-ph"
],
"title": "A \"black-box\" re-weighting analysis can correct flawed simulation data, after the fact",
"url": "https://arxiv.org/abs/physics/0609194"
},
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"source": {
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